A project on achieving Named-Entity Recognition using Deep Learning.
As the page on Wikipedia says, Named-entity recognition (NER) (also known as entity identification, entity chunking and entity extraction) is a subtask of information extraction that seeks to locate and classify named entities in text into pre-defined categories such as the names of persons, organizations, locations, expressions of times, quantities, monetary values, percentages, etc.
Take a look at this example:
Jim bought 300 shares of Acme Corp. in 2006.
Applying method of NER method, we must get:
[Jim]Person bought 300 shares of [Acme Corp.]Organization in [2006]Time.
I am doing project under the guidance of Dr. A. K. Singh. I will be adding all relevant work I do regarding this project. Check out all the subfolders for my work.